This application relates to pacing control of ad delivery for online ad campaigns.
Increasingly, advertising is being integrated with online content. Online audiences are demanding free content or at least content delivered at below market prices. Because of this demand, publishers and content networks may be delivering ads with such content to compensate for lost profits. The delivery of online ads may be through various channels, such as search, mobile search, display, mobile display, and native advertising.
One way to make use of the variety of online advertising channels is through a unified approach to digital advertising (e.g., Yahoo Ad Manager and Ad Manager Plus). Such a unified approach can reduce some of the issues faced with online advertising. For example, online advertising can be fragmented and difficult to ascertain. A unified approach can be customer-friendly by making access to various advertising channels through a unified interface. This allows customers to target and even retarget audiences seamlessly through various channels. However, by unifying various channels, analysis and enhancement of such a unified marketplace can be extremely complex and difficult to model.
To make matters even more complex, advertising can be supplied through auction-based advertising exchanges. A demand-side platform (DSP) can receive tens of billions of ad requests a day from several of Supply-Side Platforms (SSPs). Each ad impression can be traded with a different price through an auction, making enhancements and modeling extraordinarily difficult. In such a market, DSPs are parties who act as agents for advertisers and manage ad campaigns through direct buying ad-networks and/or real-time bidding (RTB) ad exchanges in order to acquire different ad impressions.
Some expectations of a DSP can include reaching delivery and performance goals of a campaign, executing a budget spending plan, and reducing creative serving costs. Reaching delivery and performance goals may include using a budget to have an extensive reach while meeting campaign performance goals. For example, in performance driven campaigns, the expectation may be to meet a performance goal while spending as much budget as possible. Execution of a budget spending plan usually includes goals of having a sustainable impact, increasing synergy with other medias, and distributing ads smoothly throughout a purchased period in order to reach a wider range of audiences. For example, an advertiser may expect a budget for a campaign to be spent evenly throughout time slots of the campaign. Reducing creative serving cost may also be a criterion. This criterion is even more important nowadays that more and more ad campaigns are in the form of video or rich media. The creative serving costs of these types of impressions can be as much as premium inventory costs, so the advertisers may desire to reduce costs by being more selective about their ad impressions.
It is increasingly challenging to meet the aforementioned expectations, especially meeting them simultaneously. Additionally, a campaign can have its own budget, budget spending plan, targeted audiences, performance goals, and creative serving costs. Also, an increasing number of DSPs compete with each other to acquire inventory through auctions, which can cause price elasticity and bid landscape between demand and supply to change frequently. Such variations can make campaign enhancement difficult. Additionally, the rapid growth of emerging online industries, such as mobile applications and user-generated content platforms, has led to increasing complexity in managing DSPs.
Additionally, with regard to pacing, advertisers look for maximizing campaign performance goals within budget schedules. Often customers prefer to impose delivery constraints to spend budget consistently and reach a wider range of audiences, and still have a sustainable impact on audiences. Also, since impressions and clicks are traded through auctions across many ad exchanges in a DSP, pricing on impressions and clicks can change rapidly and dynamically, as can the supply and demand for advertising opportunities online. Therefore, it can be challenging to perform pacing control and maximize the campaign performance simultaneously.
There is, therefore, a set of engineering problems to be solved in order to enhance management of DSPs, provide pacing control, and maximize campaign performance, simultaneously. The novel technologies described herein set out to solve such problems, which are technical considering the vast reach and scope of a DSP. Without adequate solutions to such problems, server-side and network resources can be quickly exhausted and costs of maintaining such resources can rise exponentially with the expansion of a DSP. Furthermore, the novel technologies described herein set out to solve the problem of overly complex modeling that can even occur in single-channel ad campaigns. At this point, there is room for improving DSPs, pacing control, and campaign performance.